Wind farm power curve modeling using adaptive neuro-fuzzy inference systems

—Wind power is an important renewable energy source which is currently experiencing rapid global growth. As the penetration of wind power into electricity grids increases, the need for accurate modeling and forecasting of this inherently variable source of power becomes essential. In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) approach to wind farm power curve modeling is presented. Results from a case study demonstrate the advantages of defining fuzzy inference system parameters using intuitive IF-THEN rules and initial membership function allocations compared to a purely “black box” ANFIS modeling approach.